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The Smartphone as Enabler for Road Traffic Information Based on Cellular Network Signalling
Linköping University, Department of Science and Technology. Linköping University, The Institute of Technology.ORCID iD: 0000-0002-5961-5136
Linköping University, Department of Science and Technology. Linköping University, The Institute of Technology.
2012 (English)Manuscript (preprint) (Other academic)
Abstract [en]

The higher penetration rate of GPS-enabled smartphones together with their improved processing power and battery life makes them suitable for a nu mber of participatory sensing applications. The purpose of this paper is to an alyse how GPS-enabled smartphones can be used in a participatory sensingcontext to build a radio map for RSS-based positioning, with a special focus on road traffic information based on cellular network signalling.

The CEP-67 location accuracy achieved is 75 meters for both GSM and UMTS using Bayesian classification. For this test site, the accuracy is similar for GSM and UMTS, with slightly better results for UMTS in the CEP-95 error metric.

The location accuracy achieved is good enough to avoid large errors in travel time estimation for highway environments, especially considering the possibility to filter out estimates with low accuracy using for example the posterior bin probability in Bayesian classification. For urban environments more research is required to determine how the location accuracy will affect the path inference problem in a dense road network. The location accuracy achieved in this paper is also sufficient for other traffic information types, for example origin-destination estimation based on location area updates.

Place, publisher, year, edition, pages
2012.
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:liu:diva-87739OAI: oai:DiVA.org:liu-87739DiVA: diva2:599847
Available from: 2013-01-22 Created: 2013-01-22 Last updated: 2016-05-04Bibliographically approved
In thesis
1. Generating Road Traffic Information Based on Cellular Network Signaling
Open this publication in new window or tab >>Generating Road Traffic Information Based on Cellular Network Signaling
2013 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Cellular networks of today generate a massive amount of signalling data. A large part of this signalling is generated to handle the mobility of subscribers, irrespective of the subscriber actively uses the terminal or not. Hence it contains location information that can be used to fundamentally change our understanding of human travel patterns.

This thesis aims to analyse the potential and limitations of using this signalling data in the context of road traffic information, i.e. how we can estimate the road network traffic state based on standard signalling data already available in cellular networks. This is achieved by analytical examination and experiments with signalling data and measurements generated by standard cell phones.

The thesis describes the location data that is available from signalling messages in GSM, GPRS and UMTS networks, both in idle mode and when engaged in a telephone call or a data session. The signalling data available in a ll three networks is useful to estimate traffic information, although the resolution in time and space will to a large extent depend on in which mode the terminal is operating.

Spatial analysis of handover signalling data has been performed for terminals engaged in telephone calls. The analysis indicates that handover events from both GSM and UMTS networks can be used as efficient input to systems for travel time estimation, given that route classification and filtering of non -vehicle terminals can be solved.

By analysing signalling data and received signal strength (RSS) measur ements from cell phones, it can be seen the route classification problem in the context of estimating travel times based on handover events is non -trivial even for highway environments. However, it is presented that the problem can be sa tisfactory solved for highway environments by using basic classification methods, like for example Bayesian classification.

Furthermore the thesis points out that the new era of smartphones can be an enabler for road traffic information from cellular networks in the close future. By examining measurements collected by a smartphone client, it is illu strated how the radio map for cell phone positioning can be built by participatory sensing. It is also shown that the location accuracy of RSS-based cell phone positioning is accurate enough to p rovide both travel time and OD-matrix estimation.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2013. 40 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1577
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-87740 (URN)978-91-7519-693-0 (ISBN)
Presentation
2013-01-25, K1, Kåkenhus, Campus Norrköping, Linköpings universitet, Norrköping, 13:15 (English)
Opponent
Supervisors
Available from: 2013-01-22 Created: 2013-01-22 Last updated: 2016-05-04Bibliographically approved

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Gundlegård, DavidKarlsson, Johan M

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